About the Role
This role involves leading the design and implementation of data systems that power personalization features, enabling intelligent user experiences through scalable machine learning integration and robust data infrastructure.
Responsibilities
- Lead the development of scalable data architectures for personalization platforms
- Design and implement data pipelines that support machine learning workflows
- Collaborate with data scientists to productionize models and algorithms
- Optimize data storage and retrieval for low-latency applications
- Ensure data quality and consistency across personalization systems
- Work closely with product and analytics teams to define key metrics
- Drive best practices in data modeling and engineering standards
- Mentor junior engineers and promote technical excellence
- Evaluate and integrate new data technologies and tools
- Support A/B testing and experimentation frameworks
- Monitor system performance and troubleshoot production issues
- Contribute to roadmap planning for data infrastructure
- Maintain documentation for data models and pipelines
- Ensure compliance with data governance policies
- Improve data processing efficiency and reduce latency
- Build reusable components for feature engineering
- Integrate real-time data streams into decision systems
- Collaborate on cross-team initiatives involving data sharing
- Support scalable deployment of machine learning models
- Use data to inform product personalization strategies
- Implement data validation checks across pipelines
- Work with cloud-based data platforms and services
- Ensure systems are designed for high availability
- Contribute to incident response and root cause analysis
- Promote data-driven decision-making across teams
Nice to Have
- Master’s degree in computer science, data science, or related field
- Experience in gaming, sports, or entertainment industries
- Prior leadership role in data science engineering
- Contributions to open-source data or ML projects
- Experience with real-time bidding or ad tech systems
- Knowledge of reinforcement learning applications
- Familiarity with user behavior modeling
- Experience with large-scale A/B testing platforms
- Background in distributed systems design
- Published work in data engineering or ML conferences
Compensation
Competitive salary and benefits package
Work Arrangement
Hybrid
Team
Part of the data science and engineering team focused on personalization and user engagement
About the Team
The team focuses on delivering personalized content and experiences using data science and engineering solutions. It operates at the intersection of machine learning, data infrastructure, and product innovation to drive user engagement.
What You’ll Do
- Design and maintain data pipelines that support real-time personalization models.
- Collaborate with data scientists to deploy and monitor ML models in production.
- Lead technical strategy for data architecture within the personalization domain.
Not specified
